Smart Maintenance

The digital transformation, especially the shift of maintenance to smart maintenance, contains a number of challenges. The management of data plays a significant role in this [1]. The use of sensor technology and devices for mobile data acquisition offers a variety of possibilities for quickly capturing large amounts of data, even in real time. In this context, however, there is also a need for tools that enable efficient data exchange and, at the same time, structured storage of large amounts of data. One of these tools is the digital lifecycle record, which has enormous potential for data-driven services thanks to its special features.

Digitization of industrial production processes allows the introduction of datadriven business models using Cyber Physical Systems (CPS) and Industrial Internet of Things (IIoT). To ensure efficient manufacturing, production systems must be able to communicate and interact with their environment, to monitor wear conditions, and to selfadapt their behavior to a given situation. This article gives an overview about the historical development of intelligent production systems with focus on condition monitoring and predictive maintenance in an availability oriented business model.

Standards are becoming more and more important in maintenance, particularly as a result of the changes in Industry 4.0. The vision of Smart Maintenance describes a predictive maintenance which, with the help of digital technologies, ensures the availability of the highly automated systems. The collaboration in maintenance of all actors within the asset life cycle (manufactures, operators, service providers, etc.) depends on agreed standards on technological and organizational aspects. And it’s only with a coordinated asset management that the idea of Industry 4.0 will fly.